Model comparison / LiveBench snapshot

Ox Alpha vs Gemini

Compare the public ox-alpha-max leaderboard record with the six Gemini records in the same LiveBench snapshot, then decide which route deserves a test in your own coding or agentic workflow.

Snapshot: LiveBench-2026-06-25Reviewed: 1 November 2026CTA: Tokenra
01 / Quick answer

Gemini leads this public snapshot on Overall; test the route before deciding.

The Pro-tier row, gemini-3.1-pro-preview-high, is listed at 77.0 Overall on LiveBench-2026-06-25, compared with 69.2 for the ox-alpha-max label. Five of the six Gemini rows have a higher Overall score than ox-alpha-max; only the Flash-Lite row (63.9) is lower. The Pro row also scores higher in six of the seven categories. ox-alpha-max is listed higher on Agentic Coding (52.6 versus 44.1), although the 3.7 and 3.8 Flash rows score higher there. That is a useful shortlist signal, not a universal ranking of every API route or application.

Decision rule: choose Gemini as the first benchmark hypothesis if the published snapshot is your main criterion, and compare the Pro row with the Flash row that fits your latency and budget. Choose Ox Alpha when you specifically need to evaluate the Tokenra route and its behavior on your own representative workload; its listed Agentic Coding score is a reason to include it in an agentic test, not a result for your tools.
02 / Scope and names

One product, several public identifiers; seven benchmark records.

On this site, ox-alpha-max and ox-alpha refer to the same Ox Alpha product under different public naming contexts. The LiveBench row is named ox-alpha-max; the Tokenra API reference uses ox-alpha.

Gemini is a model family rather than a single model. LiveBench-2026-06-25 lists six Gemini rows across the Pro, Flash, and Flash-Lite tiers. All six labels end in -high, which LiveBench’s model metadata lists as a high reasoning-effort setting. The metadata for ox-alpha-max lists no reasoning-effort setting, and it links that label to the OpenRouter listing for stealth/ox-alpha rather than to Tokenra. The evidence remains scoped: the leaderboard shows labels and a release snapshot, not every provider, request setting, or raw artifact behind a row.

Comparison scope and access boundary
DimensionOx AlphaGemini
Leaderboard labelsox-alpha-maxgemini-3.1-pro-preview-high gemini-3.5-flash-high gemini-3.5-flash-lite-high gemini-3.6-flash-high gemini-3.7-flash-high gemini-3.8-flash-high
Reasoning effort in metadataNot listedHigh (-high suffix)
Documented API contextTokenra Chat Completions routeVerify current Google Gemini API documentation
Benchmark identityPublic label-level observationPublic label-level observation
Commercial priceCheck Tokenra live terms; see the pricing pageCheck Google live pricing
03 / LiveBench data

Gemini rows lead on Overall; agentic coding and data analysis are mixed.

The following values are derived from the LiveBench release data for LiveBench-2026-06-25 (task scores and category definitions), reviewed 1 November 2026. Each category value is the mean of that category’s task scores, and Overall is the mean of the seven category values, rounded to one decimal. The same method reproduces the ox-alpha-max values on the benchmark page.

LiveBench-2026-06-25 values for ox-alpha-max and six Gemini rows, sorted by Overall
Model rowOverallReasoningCodingAgenticMathDataLanguageIF
Gemini 3.7 Flash78.887.878.958.393.568.085.579.9
Gemini 3.1 Pro77.084.076.544.191.078.585.479.1
Gemini 3.8 Flash75.889.372.554.291.654.087.881.4
Gemini 3.5 Flash74.682.078.249.088.264.984.675.6
Gemini 3.6 Flash73.685.177.943.486.463.083.975.4
Ox Alpha69.276.675.852.677.575.866.160.3
Gemini 3.5 Flash-Lite63.960.276.145.373.753.271.867.2

Ox Alpha is the ox-alpha-max row. Agentic = Agentic Coding, Math = Mathematics, Data = Data Analysis, IF = Instruction Following. Each Gemini row is the leaderboard label with the gemini- prefix and -high suffix listed in the scope table above; gemini-3.1-pro-preview-high appears as Gemini 3.1 Pro.

Important: LiveBench also displays a “cost per successful task” field. This page does not compare it, because it is a benchmark metric rather than an input/output token price, provider invoice, subscription price, or free-access promise. See the benchmark methodology for the evidence standard and the pricing page for provider rates. Leaderboard releases change over time; this page uses the same snapshot as the other comparison pages so every row comes from one release.

04 / Interpretation

A leaderboard difference narrows a test; it does not replace one.

The largest listed gaps in the Gemini 3.1 Pro row’s favor are language and instruction following, followed by mathematics and reasoning, while coding is close (75.8 versus 76.5). Agentic coding points the other way for that row, and the spread across Gemini tiers is wide: Overall runs from 63.9 for Flash-Lite to 78.8 for the 3.7 Flash row. A single “Gemini” number therefore hides which tier, release, and reasoning setting you would actually call.

Do not read the table as a matched-conditions experiment. The Gemini labels are listed at a high reasoning-effort setting, while the listing for ox-alpha-max does not state one, and the leaderboard does not publish every request setting, tool policy, or provider route behind a row. For a fair application test, keep the prompt set, context selection, token budget, tools, retries, and scoring rubric fixed. Record provider route, date, model identifier, latency, failures, and actual billing separately from the LiveBench table.

05 / Use cases

When should you choose each model?

Practical starting points
If you prioritizeStart withWhy
Published benchmark scoreGeminiFive of six Gemini rows have a higher Overall value in this snapshot; the highest-listed row is a Flash tier, not Pro.
Agentic codingRun bothThe listed values are mixed: ox-alpha-max is above four Gemini rows, including Pro, and below the 3.7 and 3.8 Flash rows.
Testing the documented Ox Alpha routeOx AlphaThe Tokenra API reference provides the integration boundary to validate.
Production coding reliabilityRun bothYour own repository, prompts, tools, and failure policy determine the result.
Commercial costVerify both providersLiveBench cost/success is not API pricing; compare live rates from Tokenra and Google.

To start an actual Tokenra integration, use the Ox Alpha API reference and keep credentials server-side. For the rates Tokenra lists, see the Ox Alpha pricing page.

06 / FAQ

Ox Alpha vs Gemini questions.

Is Ox Alpha better than Gemini?

On the LiveBench-2026-06-25 snapshot, five of the six Gemini rows have a higher Overall score than ox-alpha-max, and the gemini-3.1-pro-preview-high row is higher in six of the seven categories. ox-alpha-max is listed higher on Agentic Coding than that row. The result is a leaderboard comparison, not a universal claim about every workflow or provider route.

Which Gemini models does this comparison cover?

LiveBench-2026-06-25 lists six Gemini rows: gemini-3.1-pro-preview-high, gemini-3.5-flash-high, gemini-3.5-flash-lite-high, gemini-3.6-flash-high, gemini-3.7-flash-high, and gemini-3.8-flash-high. Their Overall values range from 63.9 to 78.8, compared with 69.2 for ox-alpha-max.

Is Ox Alpha free?

The $0.000 value displayed by LiveBench is a benchmark cost-per-successful-task field. It is not a Tokenra API price or a universal free-access guarantee. See the pricing page for the per-token rates Tokenra lists.

Does the ox-alpha-max score verify the Tokenra Ox Alpha route?

No. The public leaderboard identifies the ox-alpha-max label and its snapshot values, but it does not independently publish a complete mapping to the Tokenra ox-alpha route.

Test the route you will actually use.

Read the Tokenra integration boundary before comparing production behavior.

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